BGAN

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Boundary-seeking generative adversarial networks (BGAN)

as featured in the paper: https://arxiv.org/abs/1702.08431v2

.. _email: [email protected]

.. _create a GitHub issue: https://github.com/rdevon/BGAN/issues/new

Requirements (rough estimate)

.. Fuel: http://fuel.readthedocs.io/en/latest/index.html .. Lasagne: http://lasagne.readthedocs.io/en/latest/ .. Theano (bleeding edge): http://deeplearning.net/software/theano/ .. progressbar2: http://progressbar-2.readthedocs.io/en/latest/

Basic instructions

Note: Very basic. In-depth instuctions forthcoming.

Datasets are available via Fuel: http://fuel.readthedocs.io/en/latest/built_in_datasets.html

Install MNIST:

.. code-block:: bash

$ cd <Dataset directory>

$ fuel-download binarized_mnist

$ fuel-convert binarized_mnist

Install CelebA:

.. code-block:: bash

$ cd <Dataset directory>

$ fuel-download celeba

$ fuel-convert celeba 64

Usage

For simple BGAN running on discrete MNIST:

.. code-block:: bash

python main_discrete.py -o <Output directory -S <Path to MNIST hdf5>

For simple BGAN running on continuous CelebA:

.. code-block:: bash

python main_continuous.py -o <Output directory> -S <Path to CelebA hdf5>

Basic documentation found in:

.. code-block:: bash

python main_continuous.py --help

Note: Published versions of the model are available in the code, and instructions to reproduce will be added soon.

If there are bugs or clarity is needed to run models, please add to the Issues.